AGC of restructured multi-area multi-source hydrothermal power systems incorporating energy storage units via optimal fractional-order fuzzy PID controller

• Published in: Neural computing & applications Vol. 31; no. 3; pp. 851 - 872
• Main Author: Arya, Yogendra
• Format: Journal Article
• Language: English
• Published: London Springer London 14.03.2019; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Automatic control; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Controllers; Data Mining and Knowledge Discovery; Deregulation; Electric power systems; Energy storage; Fuzzy control; Fuzzy systems; Image Processing and Computer Vision; Nonlinear control; Optimization; Original Article; Parameters; Probability and Statistics in Computer Science; Proportional integral derivative; Rechargeable batteries; Storage batteries; Storage units; Transient performance; Multi-area multi-source system; Fractional-order PID controller; Restructured power system; Automatic generation control; Fuzzy PID controller
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-017-3114-5

Owing to nonlinear structure and uncertain load demand characteristics, expert and intelligent automatic generation control (AGC) is inevitable for coherent operation and control of electric power system. Hence, in this paper, to mitigate the frequency and power deviations efficiently under sudden load demand conditions, a novel fractional-order fuzzy PID (FOFPID) controller is suggested in AGC of restructured multi-area multi-source hydrothermal power systems. The parameters of FOFPID controller are optimized by utilizing bacterial foraging optimization algorithm. The controller is implemented on restructured two- and three-area systems. It is observed that the advocated method shows superiority over fuzzy PID, fractional-order PID and conventional PID control schemes. Energy storage units such as redox flow batteries (RFB) which show extremely long charge–discharge life cycle and outstanding quick response to alleviate the system oscillations under disturbances have further been incorporated into the studied systems to analyze their efficacy in boosting AGC performance. Analysis of results reveals that with RFB, system transient performance improves significantly. It is also observed that the obtained results satiate the AGC requirement under different power transactions taking place in a deregulated market in the presence/absence of appropriate generation rate constraint treated for thermal and hydro plants. Finally, the robustness of the presented approach is demonstrated against the wide variations in the system parameters and initial loading condition.